Related papers: J-PAS: A Neural Network Approach to Single Stellar…
The JAGB method has been proposed as a distance indicator for Local Group galaxies. We investigate the populations of the J region in the (J-K,J) colour-magnitude plane of the Large and Small Magellanic Clouds (LMC and SMC), aiming to…
Despite the advances provided by large-scale photometric surveys, stellar features - such as metallicity - generally remain limited to spectroscopic observations often of bright, nearby low-extinction stars. To rectify this, we present a…
We present the Galaxy Assembly and Interaction Neural Networks (GAINN), a series of artificial neural networks for predicting the redshift, stellar mass, halo mass, and mass-weighted age of simulated galaxies based on JWST photometry. Our…
This paper is the first of a series of papers constraining cosmological parameters with weak lensing peak statistics using $\sim 450~\rm deg^2$ of imaging data from the Kilo Degree Survey (KiDS-450). We measure high signal-to-noise ratio…
Planetary nebulae (PNe) are pivotal for advancing our knowledge of stellar evolution and galactic chemical enrichment. Recent progress in surveys and data analysis has revolutionized PN research, leading to the discovery of new objects and…
We present a new method for obtaining photometric redshifts (photo-z) for sources observed by multiple photometric surveys using a combination (conflation) of the redshift probability distributions (PDZs) obtained independently from each…
We present data collected using the camera PISCES coupled with the Firt Light Adaptive Optics (FLAO) mounted at the Large Binocular Telescope (LBT). The images were collected using two natural guide stars with an apparent magnitude of R<13…
The efficiency of the transport of angular momentum and chemical elements inside intermediate-mass stars lacks proper calibration, thereby introducing uncertainties on a star's evolutionary pathway. Improvements require better estimation of…
Some of the first stars in the Universe might be powered by Dark Matter (DM) annihilations, rather than nuclear fusion. Those objects, i.e. Dark stars (DS), offer a unique window into understanding DM via the observational study of the…
We present a new method for the evaluation of the age and age-spread among pre-main-sequence (PMS) stars in star-forming regions in the Magellanic Clouds, accounting simultaneously for photometric errors, unresolved binarity, differential…
We apply machine learning in the form of a nearest neighbor instance-based algorithm (NN) to generate full photometric redshift probability density functions (PDFs) for objects in the Fifth Data Release of the Sloan Digital Sky Survey (SDSS…
Identification of specific stellar populations using photometry for spectroscopic follow-up is a first step to confirm and better understand their nature. In this context, we present an unsupervised machine learning approach to identify…
Due to the ever-expanding volume of observed spectroscopic data from surveys such as SDSS and LAMOST, it has become important to apply artificial intelligence (AI) techniques for analysing stellar spectra to solve spectral classification…
Photometric data of galaxies covering the rest-frame wavelength range from far-UV to far-IR make it possible to derive galaxy properties with a high reliability by fitting the attenuated stellar emission and the related dust emission at the…
This paper is part of large effort within the J-PAS collaboration that aims to classify point-like sources in miniJPAS, which were observed in 60 optical bands over $\sim$ 1 deg$^2$ in the AEGIS field. We developed two algorithms based on…
Photometric surveys require precise point spread function (PSF) characterization, as it varies across filters and is crucial for accurate photometry and low surface brightness (LSB) studies. However, the small PSF size provided by default…
The PAU Survey (PAUS) is an innovative photometric survey with 40 narrow bands at the William Herschel Telescope (WHT). The narrow bands are spaced at 100\AA\ intervals covering the range 4500\AA\ to 8500\AA\ and, in combination with…
We present a Bayesian method to determine simultaneously the age, metallicity, distance modulus, and interstellar reddening by dust of any resolved stellar population, by comparing the observed and synthetic color magnitude diagrams on a…
The discovery both through spectroscopy and photometry of multiple stellar populations in Galactic globular clusters, and in Magellanic Clouds' massive intermediate-age and old clusters, has led to a major change in our views about the…
In this paper, we present a deep learning system approach to estimating luminosity, effective temperature, and surface gravity of O-type stars using the optical region of the stellar spectra. In previous work, we compare a set of machine…